Typical Method Research Articles

Investigating flocculation mechanisms and ecological safety of cationic guar gum for rapid harvesting of microalgal cells

Addressing the drawbacks of traditional flocculants on microalgae biomass harvesting is crucial for large-scale industrial applications of microalgae production. In this study, cationic bioflocculant was successfully prepared by introducing cationic groups into the side chain of guar gum, achieving in-situ algae flocculation efficiency of 83.5 % with the dosage of 18.0 mg/L under pH = 10.0. Through a harmonious integration of predictive modelling and practical experimentation, a superior cell flocculation capacity of 23.5 g/g was achieved. In addition, the environmental safety and biocompatibility of cationic guar gum was assessed, using the typical suspension quantitative bacteriostatic method and the fluorescent double-staining technique. The results showed that the inhibition efficiency of Staphylococcus aureus in the system containing 60.0 mg/L cationic guar gum was only 12.0 % and there was no inhibition against Escherichia coli colonies. These findings provide a safe and green flocculant for efficient microalgae harvesting and spent medium treatment.

A universal method for surface-based binding assays by preparing immobilized β2-adrenergic receptor stationary phase using solid binding peptide as a fusion tag

Protein functionalized surface has the potential to develop new assays for determining the drug-like properties of potential compounds and discovering specific partners of G protein-coupled receptors (GPCRs). However, a universal method for purifying and immobilizing functional GPCRs has remained elusive. To this end, we developed a general and rapid way to purify and immobilize β2-adrenergic receptor (β2AR) by silicon-specific peptide. We screened CotB1p as a tag from six silica-binding peptides (minTBP-1, CotB1p, SB7, Car9, and Si4–1) by examining their affinity to macroporous silica gel. We investigated the adsorption and desorption of CotB1p-tagged β2-adrenoceptor (β2AR-CotB1p) under diverse conditions to propose a protocol for receptor purification and immobilization. Under optimized conditions, β2AR immobilization were achieved by directly immersing cell lysates harboring the receptor with silica gel, and the elution of the receptor without demonstratable contaminants was realized by including l-arginine/L-lysine in the elutes. This allows purification of the receptor from Escherichia coli (E.coli) lysates with a purity of 95 %. The immobilized receptor was utilized as a stationary phase to reveal the tag impact on ligand-binding outputs by comparing the CotB1p-strategy with a typical covalent method. The KAs of salbutamol, chlorprenaline, tulobuterol, and terbutaline on β2AR-CotB1p column were 1.26 × 106, 6.59 × 106, 7.90 × 106, and 8.97 × 105 M−1 respectively, which were two orders of magnitude higher than those on the Halo-β2AR column. The whole immobilization was accomplished within 30 min without the requirement of any special treatment, resulting in enhanced accuracy for determining receptor-ligand binding parameters. Taken together, CotB1p-mediated strategy is simple, rapid, and universal for purification or immobilization of unstable biomolecules like GPCRs for analytical and biological applications.

High dimensional discriminant rules with shrinkage estimators of the covariance matrix and mean vector

Linear discriminant analysis (LDA) is a typical method for classification problems with large dimensions and small samples. There are various types of LDA methods that are based on the different types of estimators for the covariance matrices and mean vectors. In this paper, we consider shrinkage methods based on a non-parametric approach. For the precision matrix, methods based on the sparsity structure or data splitting are examined. Regarding the estimation of mean vectors, Non-parametric Empirical Bayes (NPEB) methods and Non-parametric Maximum Likelihood Estimation (NPMLE) methods, also known as f-modeling and g-modeling, respectively, are adopted. The performance of linear discriminant rules based on combined estimation strategies of the covariance matrix and mean vectors are analyzed in this study. Particularly, the study presents a theoretical result on the performance of the NPEB method and compares it with previous studies. Simulation studies with various covariance matrices and mean vector structures are conducted to evaluate the methods discussed in this paper. Furthermore, real data examples such as gene expressions and EEG data are also presented.

Phase stability of W-containing high-entropy carbide with silicon addition at high temperatures

Reactive melt infiltration (RMI) is a typical method to produce carbon fiber-reinforced ultra-high temperature ceramic matrix composites (Cf/UHTCs), for which the molten Si is a very general and practical infiltrator. High-entropy carbide (HE-carbide) is a newly developed promising matrix phase of Cf/UHTCs. Understanding the phase equilibrium relation in the HE-carbide and Si reaction system can provide accurate guidance on designing the RMI process for preparing HE-carbide matrix composites with controlled phases and microstructure. This study systematically investigates W-containing HE-carbide and Si addition reactions at high temperatures. Samples with nominal starting compositions of (Ti0.2Zr0.2Hf0.2Ta0.2W0.2)C-xSi (HEC-xSi, x = 2.5, 5 and 10 wt%) are prepared by spark plasma sintering technique at 1500 °C and 1700 °C with an axial pressure of 40 MPa for 10 min. The results show that adding 2.5 wt% or 5 wt% Si removes carbon from the HEC matrix, forming SiC and stable equimolar (Ti0.2Zr0.2Hf0.2Ta0.2W0.2)C1-x phase with carbon deficiency at high temperatures. In contrast, besides the SiC phase, the addition of 10 wt% Si in the HEC matrix may form unstable transient phases of (Ti0.2Zr0.2Hf0.2Ta0.2W0.2)C1-x with supersaturated carbon deficiencies at high temperatures, which finally decomposes into non-equimolar HE-carbide (Ti0.2Zr0.2Hf0.2Ta0.2W0.2-y)C1-z and metal silicide WSi2 phases. The effects of the HEC and Si reactions on the microstructure evolution of the samples during sintering are discussed. Meanwhile, the mechanical properties of the samples with the reaction resulting microstructure are measured and briefly discussed.

Probing a neural unreliability account of auditory sensory processing atypicalities in Rett Syndrome

BackgroundIn the search for objective tools to quantify neural function in Rett Syndrome (RTT), which are crucial in the evaluation of therapeutic efficacy in clinical trials, recordings of sensory-perceptual functioning using event-related potential (ERP) approaches have emerged as potentially powerful tools. Considerable work points to highly anomalous auditory evoked potentials (AEPs) in RTT. However, an assumption of the typical signal-averaging method used to derive these measures is “stationarity” of the underlying responses – i.e. neural responses to each input are highly stereotyped. An alternate possibility is that responses to repeated stimuli are highly variable in RTT. If so, this will significantly impact the validity of assumptions about underlying neural dysfunction, and likely lead to overestimation of underlying neuropathology. To assess this possibility, analyses at the single-trial level assessing signal-to-noise ratios (SNR), inter-trial variability (ITV) and inter-trial phase coherence (ITPC) are necessary.MethodsAEPs were recorded to simple 100 Hz tones from 18 RTT and 27 age-matched controls (Ages: 6–22 years). We applied standard AEP averaging, as well as measures of neuronal reliability at the single-trial level (i.e. SNR, ITV, ITPC). To separate signal-carrying components from non-neural noise sources, we also applied a denoising source separation (DSS) algorithm and then repeated the reliability measures.ResultsSubstantially increased ITV, lower SNRs, and reduced ITPC were observed in auditory responses of RTT participants, supporting a “neural unreliability” account. Application of the DSS technique made it clear that non-neural noise sources contribute to overestimation of the extent of processing deficits in RTT. Post-DSS, ITV measures were substantially reduced, so much so that pre-DSS ITV differences between RTT and TD populations were no longer detected. In the case of SNR and ITPC, DSS substantially improved these estimates in the RTT population, but robust differences between RTT and TD were still fully evident.ConclusionsTo accurately represent the degree of neural dysfunction in RTT using the ERP technique, a consideration of response reliability at the single-trial level is highly advised. Non-neural sources of noise lead to overestimation of the degree of pathological processing in RTT, and denoising source separation techniques during signal processing substantially ameliorate this issue.

Thermal Safe Power Constrained Dynamic Mapping for Heterogeneous Multicore System

Heterogeneous multicore system could provide high flexibility for applications through integrating different types of cores. As the number of cores increases, more and more transistors are integrated which could lead to the rise of chip temperature, thus have a negative impact on the system performance. At present, the typical method to tackle this problem is dynamic voltage and frequency scaling (DVFS) which reduces the voltage and frequency to achieve cooling. However, DVFS will make the heterogeneous multicore system unable to take full advantage of its performance. This paper proposes a dynamic mapping method called TspDM which maximizes the system performance target under the premise of satisfying the temperature safety power. TspDM exploits the runtime performance counters of running threads to dynamically adjust thread mapping. Specifically, a lightweight Artificial Neural Network (ANN) model is proposed to obtain the thread-to-core type mapping when a remapping process is activated. Subsequently, TspDM determines the specific core locations of threads according to the number of threads mapped to a certain core type and the thermal safety power computation. The experimental results show that the proposed method is 21% better than that of PCMig while ensuring the thermal safety of heterogeneous platform. In addition, TspDM outperforms recent performance constrained and power constrained literature in terms of system throughput.

The effect of methylene blue on water hardness and antibacterial activity and the environment

This research was carried out to compare complexometric titration methods for the determination of water hardness in the presence of two colored indicators. The complexometric titration with EDTA method has evolved from the typical method of determining water hardness rates used in various references in several countries. Our objective is to make a comparison between Methylene Blue (MB) and Eriochrome black T (EBT) used as color indicators to determine the hardness in drinking water as a function of the flow. Several chemical – physic were used to determine the maximum absorbance of the two dyes UV-visible, identification of functional groups by infrared spectroscopy (FT-IR), supported by the effect of concentration conductivity, pH and turbidity and density. Test results to determine water hydrometric title (TH) in the presence of two colored indicators indicated that the equivalent volume values (Veq) are doubled for the BM indicator compared to the EBT indicator however with impressive TH values in two different intervals between 10 < TH< 20 and 30 < TH < 50. This shows that the colored indicator Methylene Blue has important differences. An antibacterial activity is observed on the dye by the disk method on four bacteria in the agar culture medium, from which it can be said that there is sensitivity to antimicrobial agents against methylene blue.

Micromechanical analysis of fiber-reinforced ceramic matrix composites by a geometrically nonlinear hierarchical quadrature element model

The stress fields of fiber-reinforced ceramic matrix composites (CMCs) under longitudinal tension are predicted using a non-linear hierarchical quadrature element method (HQEM) in this work. The HQEM combines the differential quadrature method (DQM) with the hierarchical finite element method (HFEM), which is a typical p-version finite element method (FEM). High-order interpolation functions of the HQEM allow accurate evaluation of stress distribution. Fiber, matrix, and interfaces of the CMCs are modeled as linear elastic materials that may have large displacements. The nonlinear HQEM estimation of CMCs stress distributions are validated by comparing with analytical results obtained using classical BHE shear-lag model. Stress distribution in three characteristic stages in the damage evolution process, namely, interface perfectly bonded, interface debonding, and fiber failure are investigated. It is shown that when fiber failure happens, geometric non-linearity must be considered to avoid excessive stress concentration. Furthermore, the stress distribution within three-dimensional cylindrical CMCs cell is studied, which sheds light on the future exploration of three-dimensional CMCs analyses.

Enhancing the thermoelectric and mechanical properties of Cu3SbSe4-based materials by defect engineering and covalent bonds reinforcement

Here, a typical microwave hydrothermal-assisted synthesis method is utilized to fabricate Co/Sn co-doped Cu3SbSe4 materials. Experimental results demonstrate that the formation of a nanoscale Co9Se8 phase occurs when the solid solubility of Co is exceeded. This phase effectively enhances phonon scattering at the grain boundary's high-density dislocation region, leading to a significant reduction in lattice thermal conductivity. Simultaneously, the interface between Co9Se8 and Cu3SbSe4 exhibits an energy filtering effect, resulting in an improved Seebeck coefficient. The maximum zT value of 0.62 is achieved in the Cu3Sb0.96Co0.04Se4 sample. To further regulate the carrier concentration, Sn atoms are introduced, leading to peak power factor and zT values of 865.98 μW·m−1·K−2 and 0.72, respectively. The incorporation of Co and Sn doping contributes to the enhancement of mechanical properties by reinforcing covalent bonds. Mechanical property testing of the materials indicates an improvement in mechanical performance upon doping with Co and Sn. This study provides valuable insights into the in-situ introduction of a second phase through element doping, thereby enhancing the comprehensive thermoelectric properties of Cu3SbSe4-based materials. Moreover, it establishes an experimental foundation for subsequent investigations into the materials' mechanical properties.

Die Casting of Lightweight Thin Fin Heat Sink Using Al-25%Si

The demand for lightweight and cost-effective heat sinks is increasing. A typical method for economically manufacturing complex-shape heat sinks is die casting. To reduce the weight of the die-cast heat sinks, thinning the fins and base is common practice. We experimented with casting heat sinks using Al-25%Si in a conventional die casting machine with the aim of economically producing thinner fins and bases. Compared with the aluminum alloy used in conventional die casting, Al-25%Si has superior fluidity, which is proven to be very useful for reducing the thickness of the fins and base. As a result, we successfully reduced the heat sink weight using Al-25%Si and a conventional die casting machine. To investigate the properties of the produced Al-25%Si thin fin heat sink, we compared the effects of fin thickness, fin height, number of fins, and base thickness on heat dissipation and weight reduction. Additionally, we compared the weight and heat dissipation properties with those of a commercial heat sink and found that our Al-25%Si heat sink maintains the same heat dissipation performance but for 35% lower weight.

Adaptive event-triggered optimal [formula omitted] tracking control for uncertain nonlinear systems: Comparative analysis applied to autonomic tractor-trailer system

In this paper, an event-triggered tracking optimization control method is proposed for nonlinear uncertain systems with H∞ discounted cost. First, the linearization method using the infinite series expansion theorem is given. And the tracking control design problem is solved by appropriate state augment. Secondly, the zero sum differential game strategy is introduced to address the control design problem of uncertain systems with event-triggered inputs. The actor-critic-disturbance networks framework is used to approximate the optimization of event- triggered controller strategy, optimization costs, and the disturbance strategy, respectively. Due to the consideration of discrete time and continuous time dynamics, we put the impulsive system method to use and choose appropriate Lyapunov functions to prove stability and boundedness, at the same time, there will be no infinite triggering situation. Finally, the effectiveness of the proposed scheme is demonstrated by an example of a practical tractor system with n trailers through simulation compared with another typical design method.

Fast adaptive focusing confocal Raman microscopy for large-area two-dimensional materials

Large-area two-dimensional (2D) materials possess significant potential in the development of next generation semiconductor due to their unique physicochemical properties. Confocal Raman spectroscopy (CRM), a typical 2D material characterization method, has a limited effective measurement area owing to the restricted focus depth of the system and the less-than-ideal level of the substrate. We propose fast adaptive focusing confocal Raman microscopy (FAFCRM) to realize real-time focusing detection for large-area 2D materials. By observing spot changes on the charge coupled device (CCD) caused by placing an aperture in front of the CCD, the methodology gives a focusing resolution up to 100 nm per 60 μm without axial scanning. A graphene was measured over 25.6 mm × 25.6 mm area on focus through all the scanning. The research results provide new perspectives for non-destructive characterization of 2D materials at the inch level.

Performance analysis of an optimized PID-P controller for the position control of a magnetic levitation system using recent optimization algorithms

As industrial technology advances, there is an increasing need for very precise position control mechanisms for highly integrated and accurate products. Therefore, high precision positioning systems play an essential part in today's manufacturing processes. Piezoelectric actuators offer the requisite stiffness and positioning precision, but they have a limited traveling range. The combination of a linear motor with air bearings is a typical method for achieving long stroke movement at high speeds. However, to accomplish extensive and precise motion in several degrees of freedom with a linear motor and non-contact bearing, a sophisticated system setup is required. In this paper, a proportional-integral-derivative-proportional (PID-P) controller is presented for magnetic levitation system position control. Particle swarm optimization (PSO) and Black window optimization (BWO) algorithms are proposed for tuning the PID-P controller parameters. The PSO and BWO algorithms are employed by considering Integral Time Absolute Error (ITAE) as an objective function with rise-time and percentage peak overshoot as constraints. Furthermore, the performance of PSO and BWOA tuned PID-P controllers is compared to conventional PID-P and PID controllers using time response specifications such as rise time, settling time, and percentage peak overshoot. The graphical and numerical simulation results show that the PSO and BWOA tuned PID-P controller outperforms the conventional PID-P and PID controllers. The BWOA tuned PID-P controller outperformed the PSO tuned PID controller and the classical PID-P controller by 8.5 % in rise time, 46.77 % in settling time, and 86.6 % in percentage peak overshoot.

Improved typical scenario-based distributionally robust co-dispatch of energy and reserve for renewable power systems considering the demand response of fused magnesium load

In recent years, the penetration of solar and wind power has rapidly increased to construct renewable energy-dominated power systems (RPSs). On this basis, the forecasting errors of renewable generation power have negative effects on the operation of the power system. However, traditional scheduling methods are overly dependent on the generation-side dispatchable resources and lack uncertainty modeling strategies, so they are inadequate to tackle this problem. In this case, it is necessary to enhance the flexibility of the RPS by both mining the load-side dispatchable resources and improving the decision-making model under uncertainty during the energy and reserve co-dispatch. In this paper, due to the great potential in facilitating the RPS regulation, the demand response (DR) model of fused magnesium load (FML) is first established to enable the deeper interaction between the load side and the whole RPS. Then, based on the principal component analysis and clustering algorithm, an improved typical scenario set generation method is proposed to obtain a much less conservative model of the spatiotemporally correlated uncertainty. On this basis, a two-stage distributionally robust optimization model of the energy and reserve co-dispatch is developed for the RPS considering the DR of FML. Finally, the proposed method is validated by numerical tests. The results show that the costs of day-ahead dispatch and re-dispatch are significantly decreased by using the improved typical scenario set and considering the DR of FML in regulation, which enhances the operation economy while maintaining the high reliability and safety of the RPS.

Accurate kinematic calibration of a six-DoF serial robot by using hybrid models with reduced dimension and minimized linearization errors

PurposeIn typical model-based calibration, linearization errors are derived inevitably, and non-negligible negative impact will be induced on the identification results if the rotational kinematic errors are not small enough or the lengths of links are too long, which is common in the industrial cases. Thus, an accurate two-step kinematic calibration method minimizing the linearization errors is presented for a six-DoF serial robot to improve the calibration accuracy.Design/methodology/approachThe negative impact of linearization on identification accuracy is minimized by removing the responsible linearized kinematic errors from the complete kinematic error model. Accordingly, the identification results of the dimension-reduced new model are accurate but not complete, so the complete kinematic error model, which achieves high identification accuracy of the rest of the error parameters, is combined with this new model to create a two-step calibration procedure capable of highly accurate identification of all the kinematic errors.FindingsThe proportions of linearization errors in measured pose errors are quantified and found to be non-negligible with the increase of rotational kinematic errors. Thus, negative impacts of linearization errors are analyzed quantitatively in different cases, providing the basis for allowed kinematic errors in the new model. Much more accurate results were obtained by using the new two-step calibration method, according to a comparison with the typical methods.Originality/valueThis new method achieves high accuracy with no compromise on completeness, is easy to operate and is consistent with the typical method because the second step with the new model is conveniently combined without changing the sensors or measurement instrument setup.

Chattering Free Sliding-Mode Controller Design for Underactuated Tower Cranes With Uncertain Disturbance

Tower cranes are widely used in various industrial sites and require a high level of anti-disturbance performance from the crane controller due to the variability of the application environment. Although sliding mode control is a typical anti-disturbance control method, most sliding mode controllers suffer from output chattering and do not reflect well under severe external disturbances. To address these issues from a practical application perspective, a finite time sliding mode control method using the super-twisting algorithm (STA) is proposed for underactuated tower cranes operating in the presence of external disturbances. The proposed method includes a finite-time chattering-free sliding mode controller that eases the output torque chattering problem and a finite-time sliding mode observer based on STA to observe the uncertain disturbances. The observed values are then applied to the controller through feedforward compensation. Experimental results show that the proposed control method effectively weakens output torque chattering, compensates for disturbance quickly, and accurately completes control tasks.

Size Control of Carbon Xerogel Spheres as Key Factor Governing the H2O2 Selectivity in Metal-Free Bifunctional Electro-Fenton Catalysts for Tetracycline Degradation.

Carbon xerogel spheres co-doped with nitrogen and eco-graphene were synthesized using a typical solvothermal method. The results indicate that the incorporation of eco-graphene enhances the electrochemical properties, such as the current density (JK) and the selectivity for the four transferred electrons (n). Additionally, nitrogen doping has a significant effect on the degradation efficiency, varying with the size of the carbon xerogel spheres, which could be attributed to the type of nitrogenous group doped in the carbon material. The degradation efficiency improved in the nanometric spheres (48.3% to 61.6%) but decreased in the micrometric-scale spheres (58.6% to 53.4%). This effect was attributed to the N-functional groups present in each sample, with N-CNS-5 exhibiting a higher percentage of graphitic nitrogen (35.7%) compared to N-CMS-5 (15.3%). These findings highlight the critical role of sphere size in determining the type of N-functional groups present in the sample. leading to enhanced degradation of pollutants as a result of the electro-Fenton process.

RF Frequency Combining for the ATLAS ECR Ion Sources

The ECR2 and ECR3 ion sources at the Argonne Tandem Linac Accelerator System (ATLAS) operate with two microwave frequencies, improving their performance over single frequency operation. A typical method for transmitting both microwave frequencies is by having two separate frequency generators with their own corresponding amplifiers. These amplifiers transmit their microwaves into the ion source using separate waveguides. Another method that is investigated is to combine the low power microwave frequencies with a splitter/combiner and input the combined signals into the high-power amplifier, where the combined signal is amplified and transmitted down a single waveguide into the ion source. These different methods for delivering microwave power with multiple frequencies are compared, focusing on the average charge state and the intensities of each of the charge states for an oxygen plasma produced by the ECR2 ion source.This work was supported by the U.S. Department of Energy, Office of Nuclear Physics, under Contract No. DE-AC02-06CH11357. This research used resources of ANL’s ATLAS facility, which is a DOE Office of Science User Facility.

Creating negative ion beams from neutral gases using a negative hydrogen ion source

A typical method to produce negative ion beams uses alkali vapour as a medium for a double charge exchange to convert incident positive (1+) beams to negative (1-) beams. Alkali vapours pose a problem in ion production as they are flammable, explosive and cause vacuum surface contamination. Thus, it is advantageous to use non-metallic vapours for charge exchange as it will prevent hazards and the contamination of vacuum surfaces and targets in which the negative ion beams are incident upon. In this paper we will describe and demonstrate the process of creating negative ion beams by impinging a 15 keV to 30 keV beam from D-Pace's TRIUMF licenced H- volume-cusp ion source (1 mA to 15 mA) onto a volume of non-metallic neutral gas (X) resulting in a single or two-step charge exchange: H- + X → H + X- or H- + X → H + X + e → H + X-. The newly created X- ion beams will be accelerated by a (1 to 20) kV electrostatic accelerator and passed through a mass spectrometer system to separate the primary H- beam from the X- beam. The two gases studied are He and H2 and we will present the magnitude of the resultant beam currents after being separated from the incident H- beam by the mass spectrometer system.

Quantitative Surface Passivation Through Drop‐on‐Demand Inkjet Printing Enables Highly Efficient Perovskite Solar Cells

AbstractDeposition of a passivation layer on top of the perovskite is proven to be an effective method for improving the efficiency and long‐term stability of perovskite solar cells (PSCs). And the spin‐coating method is the most typical and popular method developed for this purpose. However, the spin‐coating method wastes substantial passivator materials, thus the quantitative relationship between the passivator amount and the device performance cannot be obtained. Herein, a quantitative deposition method is developed through drop‐on‐demand inkjet printing to investigate the influence of 2‐adamantylamine hydrochloride (2‐ADAHCl) deposition surface density on the device performance, which is found to have a significant impact on the device performance. A low deposition surface density of 1.1 µg cm−2 does not reach its optimum passivation capability. In contrast, an excess deposition surface density of 10.1 µg cm−2 would lead to energy level mismatch and large series resistance at the perovskite/hole transport layer (HTL) interface, thus resulting in inferior device properties. At an optimum deposition surface density of 2.5 µg cm−2, perovskite surface defects are greatly suppressed, and the interfacial contact between perovskite and HTL is improved. Finally, PSCs with a high efficiency of 24.57% are achieved with improved operational and environmental stabilities.